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Record W3091369363 · doi:10.1016/j.dcn.2020.100863

A longitudinal study investigating trajectories of sensitivity to threat over time and their association with alpha asymmetry among children and adolescents

2020· article· en· W3091369363 on OpenAlexafffund
Taylor Heffer, Teena Willoughby

Bibliographic record

VenueDevelopmental Cognitive Neuroscience · 2020
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsBrock University
FundersCanadian Institutes of Health Research
KeywordsPsychologyAssociation (psychology)Developmental psychologyAsymmetryLongitudinal studyCognitive psychologyStatisticsPsychotherapist

Abstract

fetched live from OpenAlex

Research has yet to investigate trajectories of sensitivity to threat across childhood and adolescence. Further, neural associations of these trajectories remain unknown. The current 3-year study used a latent class growth curve analysis to investigate whether there were distinct trajectories of sensitivity to threat among children and adolescents over time (N = 363; age range at Time 1 = 8-14). We also examined whether alpha asymmetry (a neural index of motivational tendencies) was associated with the different trajectories. Results revealed three distinct trajectory groups (1) high-stable sensitivity to threat, (2) moderate-increasing sensitivity to threat and (3) low-stable sensitivity to threat. The high-stable sensitivity to threat group had greater right frontal asymmetry activation (i.e., greater neural avoidance motivation) than the other two groups. Additionally, females, those with higher parental education, and individuals with more advanced pubertal development (but not age) had greater odds of being part of the high-stable sensitivity to threat group compared to the other groups. Of interest, puberty rather than age may be an important indicator of heightened sensitivity to threat.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.677

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.263
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2020
Admission routes2
Has abstractyes

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